Target detection in spectral digital imagery relates to the detection of known materials with a given target spectrum from the spectral digital imagery. Target detection is useful in a variety of different applications, for example to aid in medical diagnoses, to identify soils indicative of particular types of natural resources such as oil or minerals, to identify drug smugglers in a mountainous region, or to identify any number of military and intelligence targets by way of example only.
Two of the primary challenges with existing target detection processes are the massive amounts of data and imperfect detection algorithms which require large amounts of manual verification. Existing target detection methods are extremely time intensive because the detection plane for each target on each image must be manually inspected.
For example, given that a typical target library may have 10-50 target signatures and a collection may create 50 images per day, a single day may yield 500-2500 detection planes for analysis. For a modest daily collection resulting in 500 detection planes, an analyst working eight hours would have less than one minute to inspect each detection plane. Given that inspection of the detection requires viewing both the detection plane and the original image, visual inspection of the spectra for each high-scoring pixel, preferably with additional high resolution imagery, the simple opening and viewing of the large files can require more than the available time for analysis. Accordingly, a practical real-time target detection with existing target detection processes is simply time probative.